Relevant bibliographies by topics / IBM Watson Content Analytics

Academic literature on the topic 'IBM Watson Content Analytics'

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Published: 25 July 2024

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Journal articles on the topic "IBM Watson Content Analytics"

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Leonenko, E. A., and S. V. Kunev. "RESEARCH OF THE COMPANY’S MARKETING ENVIRONMENT BASED ON DIGITAL TECHNOLOGY TOOLS AND A PROCESS FRAMEWORK." Scientific Review Theory and Practice 11, no. 7 (2021): 2122–37. http://dx.doi.org/10.35679/2226-0226-2021-11-7-2122-2137.

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The study of the marketing environment of an enterprise is one of the most difficult types of marketing activities, since it always contains an element of foreseeing a difficult and contradictory socio-economic object – the market, therefore, the content and forms of research of the marketing environment depend on the eco- nomic structure, external and internal conditions in which it is develops, and can vary significantly. In the 21st century, the processes of growth in the use of various digital tools in various areas of business are seriously accelerating. At the same time, the catalyst for these processes in 2020 was the coronavirus pandemic. However, the changes that have taken place in the rate of introduction of digital tools will not only not receive a reverse vector, but will probably be intensified already in the context of the announced reduction of quarantine measures. At the same time, the market of marketing research tools currently has full-fledged software products for a long time (ALS Base, Marketing Ana- lytic, Marketing Expert, Power analysis, BEST Marketing, etc.) that work directly in marketing or planning divisions of organizations, as well as digital online services (Google Analytics and Yadex. Metrics, IBM Watson Analitics), applications for smartphones, etc. At the same time, all digital tools imply the use of a digital footprint, which, given the still insufficient presence of Russian companies on the Internet, leads to a limitation of their use for analytical purposes. At the same time, another trend is the introduction of a digital framework, also called Scrum technology, which is a set of principles and tools that are most often used in IT development. With their help, a developer can make a workable product in iterations of limited duration, called sprints. Product capabilities are determined when planning a sprint. The short-term iteration ensures predictability of development and, at the same time, flexibility of the process.
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Tsoi, Kelvin K. F., Felix C. H. Chan, Hoyee W. Hirai, Gary K. S. Keung, Yong-Hong Kuo, Samson Tai, and Helen M. L. Meng. "Data Visualization with IBM Watson Analytics for Global Cancer Trends Comparison from World Health Organization." International Journal of Healthcare Information Systems and Informatics 13, no. 1 (January 2018): 45–54. http://dx.doi.org/10.4018/ijhisi.2018010104.

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Visual analytics is widely used to explore data patterns and trends. This work leverages cancer data collected by World Health Organization (WHO) across a hundred of cancer registries worldwide. In this study, the authors present a visual analytics platform, IBM Watson Analytics, to explore the patterns of global cancer incidence. They included 26 forms of cancers from eight different geographic regions which are United States, the United Kingdom, Costa Rica, Sweden, Croatia, Japan, Hong Kong and China (Shanghai). An interactive interface was applied to plot a choropleth map to show global cancer distribution, and line charts to demonstrate historical cancer trends over 29 years. Subgroup analyses were conducted for different age groups. With real-time interactive features, one can easily explore the data with a selection of any cancer type, gender, age group, or geographical region. This platform is running on the cloud, so it can handle data in huge volumes, and is accessible by any computer connected to the Internet. IBM Watson Analytics released a latest version named “IBM Watson Analytics New User Experience” in the end of 2016. The new version streamlined the process to add data, discover data meaning and display result visually. The authors discuss the new features in the end of this paper.
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Hoyt, Robert Eugene, Dallas Snider, Carla Thompson, and Sarita Mantravadi. "IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics." JMIR Public Health and Surveillance 2, no. 2 (October 11, 2016): e157. http://dx.doi.org/10.2196/publichealth.5810.

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Bensberg, Frank, Gunnar Auth, and Christian Czarnecki. "Einsatz von Text Analytics zur Unterstützung literaturintensiver Forschungsprozesse." Anwendungen und Konzepte der Wirtschaftsinformatik, no. 8 (December 20, 2018): 6. http://dx.doi.org/10.26034/lu.akwi.2018.3221.

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Das anhaltende Wachstum wissenschaftlicher Veröffentlichungen wirft die Fragestellung auf, wie Literaturana-lysen im Rahmen von Forschungsprozessen digitalisiert und somit produktiver realisiert werden können. Insbesondere in informationstechnischen Fachgebieten ist die Forschungspraxis durch ein rasant wachsendes Publikationsaufkommen gekennzeichnet. Infolgedessen bietet sich der Einsatz von Methoden der Textanalyse (Text Analytics) an, die Textdaten automatisch vorbereiten und verarbeiten können. Erkenntnisse entstehen dabei aus Analysen von Wortarten und Subgruppen, Korrelations- sowie Zeitreihenanalysen. Dieser Beitrag stellt die Konzeption und Realisierung eines Prototypen vor, mit dem Anwender bibliographische Daten aus der etablierten Literaturdatenbank EBSCO Discovery Service mithilfe textanalytischer Methoden erschließen können. Der Prototyp basiert auf dem Analysesystem IBM Watson Explorer, das Hochschulen lizenzkostenfrei zur Verfügung steht. Potenzielle Adressaten des Prototypen sind Forschungseinrichtungen, Beratungsunternehmen sowie Entscheidungsträger in Politik und Unternehmenspraxis.
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Guidi, Gabriele, Roberto Miniati, Matteo Mazzola, and Ernesto Iadanza. "Case Study: IBM Watson Analytics Cloud Platform as Analytics-as-a-Service System for Heart Failure Early Detection." Future Internet 8, no. 3 (July 13, 2016): 32. http://dx.doi.org/10.3390/fi8030032.

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Marshall, Thomas Edward, and Sherwood Lane Lambert. "Cloud-Based Intelligent Accounting Applications: Accounting Task Automation Using IBM Watson Cognitive Computing." Journal of Emerging Technologies in Accounting 15, no. 1 (March 1, 2018): 199–215. http://dx.doi.org/10.2308/jeta-52095.

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ABSTRACT This paper presents a cognitive computing model, based on artificial intelligence (AI) technologies, supporting task automation in the accounting industry. Drivers and consequences of task automation, globally and in accounting, are reviewed. A framework supporting cognitive task automation is discussed. The paper recognizes essential differences between cognitive computing and data analytics. Cognitive computing technologies that support task automation are incorporated into a model delivering federated knowledge. The impact of task automation on accounting job roles and the resulting creation of new accounting job roles supporting innovation are presented. The paper develops a hypothetical use case of building a cloud-based intelligent accounting application design, defined as cognitive services, using machine learning based on AI. The paper concludes by recognizing the significance of future research into task automation in accounting and suggests the federated knowledge model as a framework for future research into the process of digital transformation based on cognitive computing.
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Nagwanshi, Kapil Kumar, and Sipi Dubey. "Statistical Feature Analysis of Human Footprint for Personal Identification Using BigML and IBM Watson Analytics." Arabian Journal for Science and Engineering 43, no. 6 (July 22, 2017): 2703–12. http://dx.doi.org/10.1007/s13369-017-2711-z.

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Choi, Youngkeun, and Jae W. Choi. "Assessing the Predictive Performance of Machine Learning in Direct Marketing Response." International Journal of E-Business Research 19, no. 1 (April 7, 2023): 1–12. http://dx.doi.org/10.4018/ijebr.321458.

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This paper intends to better understand the pre-exercise of modeling for direct marketing response prediction and assess the predictive performance of machine learning. For this, the authors are using a machine learning technique in a dataset of direct marketing, which is available at IBM Watson Analytics in the IBM community. In the results, first, among all variables, customer lifetime value, coverage, employment status, income, marital status, monthly premium auto, months since last claim, months since policy inception, renew offer type, and the total claim amount is shown to influence direct marketing response. However, others have no significance. Second, for the full model, the accuracy rate is 0.864, which implies that the error rate is 0.136. Among the patients who predicted not having a direct marketing response, the accuracy that would not have a direct marketing response was 87.23%, and the accuracy that had a direct marketing response was 66.34% among the patients predicted to have a direct marketing response.
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Ahmed, Mohammed Imtyaz, and G. Kannan. "Secure End to End Communications and Data Analytics in IoT Integrated Application Using IBM Watson IoT Platform." Wireless Personal Communications 120, no. 1 (May 6, 2021): 153–68. http://dx.doi.org/10.1007/s11277-021-08439-7.

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Varenko, Volodymyr. "Operational (Online) Analytics: New Technologies and Opportunities." Ukrainian Journal on Library and Information Science, no. 9 (June 17, 2022): 10–21. http://dx.doi.org/10.31866/2616-7654.9.2022.259140.

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The aim of the article is to systematise and generalise new knowledge on operational ana­lytics and consider specific automated information systems in terms of the present and prospects for its development. The research methodology was based on the general scientific principles of unity of theory and practice, systematics, complexity, and comprehensiveness of knowledge. The use of general scientific (description, analysis, synthesis, comparison, generalisation) and special (bibliograph­ic, sample observation, grouping, content analysis) methods at the empirical and theoretical lev­els of research contributed to achieving this goal. The scientific novelty of the study is to generalise and systematise new and available knowledge on operational analytics in terms of present and prospects for its development within one study. Conclusions. The case of the International Business Machines Corporation American elec­tronic corporation (pronounced IBM, also known as IBM or «Blue Giant»), one of the world’s largest manufacturers of all types of computers and software, one of the largest providers of global information networks, the author described and analysed the species diversity and fea­tures of the use of automated information and analytical systems based on artificial intelligence, which are available today to many users, and tomorrow will become a daily reality for any com­pany. The information systems and products that IBM now offers to the Ukrainian consumer are briefly described: systems designed for analytics by areas of application; Big Data analysts; data visualisation; policy analytics; data integration systems; advanced analytics products; in­formation systems of advanced analytics based on the Internet of Things; automated systems for forecasting analytics. Attention is focused on the features and benefits of operational analytics and its capabilities in the practical plane of use. The expediency of applying certain automated information systems according to the sphere of activity and stages of information analysis is substantiated. The advantages and prospects of operational (online) analytics development in data analytics are considered.
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Dissertations / Theses on the topic "IBM Watson Content Analytics"

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Slavětínský, Radek. "Analýza cloudových řešení Business Intelligence pro SME." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-358847.

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The thesis is focused on the analysis of presently offered products supporting Business Intelligence (BI) which are affordable for small and medium-sized enterprises (SMEs). Current BI solutions available to SMEs are mostly offered via Cloud computing, specifically in the form of Software as a Service (SaaS) as it requires low initial acquisition costs. The objectives of this thesis are to analyse the work in applications for BI in cloud that can be used by SMEs and to analyse in detail the comparison the worldwide extended reporting tools distributed as SaaS in the lower price category. The theoretical part provides a description of the Cloud computing and the BI system. In the practical part are selected following products: IBM Watson Analytics, Qlik Sense Cloud, Zoho Reports, Tableau Public and Microsoft Power BI. Practical testing of these applications was based on evaluation of the selected metrics with weights calculated by using the Fuller's triangle. Analyses and the information form the basis for comparison of selected applications. The contribution of this thesis is in discovering the strengths and weaknesses of these BI solutions. The output of this thesis can be used as a source for the selection of BI applications for SMEs.
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Books on the topic "IBM Watson Content Analytics"

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International Business Machines Corporation. International Technical Support Organization, ed. IBM Watson Content Analytics: Discovering actionable insight from your content. 3rd ed. Poughkeepsie, NY: IBM Corp., International Technical Support Organization, 2014.

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Zhu, Wei-Dong Jackie. IBM Content Analytics Version 2.2: Discovering Actionable Insight from Your Content. [United States]: IBM, 2011.

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International Web Caching and Content Delivery Workshop (8th 2003 New York, N.Y.)x. Web content caching and distribution: Proceedings of the 8th International Workshop, IBM T.J. Watson Research Center, Hawthorne, New York, USA, September 29-October 1, 2003. Boston: Kluwer Academic Publishers, 2004.

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Miller, James. Learning IBM Watson Analytics. Packt Publishing, Limited, 2016.

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Book chapters on the topic "IBM Watson Content Analytics"

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Mudura, Vlad Antoniu, Francesco Frosini, and Ernesto Iadanza. "IBM Watson Analytics for Managing Congestive Heart Failure." In EMBEC & NBC 2017, 1025–28. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5122-7_256.

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Holzinger, Andreas, Christof Stocker, Bernhard Ofner, Gottfried Prohaska, Alberto Brabenetz, and Rainer Hofmann-Wellenhof. "Combining HCI, Natural Language Processing, and Knowledge Discovery - Potential of IBM Content Analytics as an Assistive Technology in the Biomedical Field." In Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, 13–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39146-0_2.

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Winters-Miner, Linda A., Pat Bolding, Thomas Hill, Bob Nisbet, Mitchell Goldstein, Joseph M. Hilbe, Nephi Walton, Gary Miner, Eric W. Brown, and Martin S. Kohn. "IBM Watson for Clinical Decision Support." In Practical Predictive Analytics and Decisioning Systems for Medicine, 1038–40. Elsevier, 2015. http://dx.doi.org/10.1016/b978-0-12-411643-6.00053-3.

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Conference papers on the topic "IBM Watson Content Analytics"

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Faizullov, Ilias, and Sergey Yablonsky. "Modern Advanced Analytics Platforms and Predictive Models for Stock Price Forecasting: IBM Watson Analytics Case." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2017. http://dx.doi.org/10.24251/hicss.2017.128.

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Tsoi, Kelvin KF, Felix CH Chan, Hoyee W. Hirai, Gary KS Leung, Yong-Hong Kuo, Samson Tai, and Helen Meng. "Data Visualization on Global Trends on Cancer Incidence An Application of IBM Watson Analytics." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2017. http://dx.doi.org/10.24251/hicss.2017.397.

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Masruroh, Siti Ummi, Asyifa Tasya Fadilah, Khodijah Hulliyah, Ahmad Fadlan Ramadhan, Rizka Amalia Putri, and Mohamad Ali Irfan. "Implementation of the K-means Clustering Algorithm for Targeting Ads. Case Study: IBM Watson Analytics Car Insurance Customer Data." In 2023 11th International Conference on Cyber and IT Service Management (CITSM). IEEE, 2023. http://dx.doi.org/10.1109/citsm60085.2023.10455449.

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Niggli, C., H.-C. Pape, and L. Mica. "Validation of IBM-WATSON Health Trauma Pathway explorer, a visual based analytics tool to predict outcomes of poly-trauma patients." In Deutscher Kongress für Orthopädie und Unfallchirurgie. Georg Thieme Verlag KG, 2020. http://dx.doi.org/10.1055/s-0040-1717426.

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Li, Qiuwen. "Text vs. Images: Understanding emotional expressions on social media during COVID-19 pandemic." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002031.

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Due to the global spread of COVID-19, people all around the world have been forced to change the way they communicate and interact with others. Keeping social distance and wearing masks helps prevent the spread of coronavirus, and also makes online social platforms increase in demand in an unprecedented way (Flynn, 2008). Prolonged social isolation during COVID-19 is likely to have negative effects on mental health and communication on an individual. Researchers have found evidence for caused and elevated anxiety disorders such as somatization, post-traumatic stress disorder, panic disorders and depression amongst individuals during the COVID-19 pandemic (Meikle, 2016). Numerous studies have found that people only show their “good side” and positive emotions on social media. How does social media reveal our anxiety disorders during Covid? Do emotions expressed in pictures match with its text content on social media? In this research, 500 most recent selfies from individual accounts between December 1st and 10th in 2021 from age ranges 13 to 55 years old were downloaded for the study. The study used IBM Watson tone analyzer and Sky-Biometry as tools for linguistic analysis and emotion detection. In addition, the research compared imagery and text content in social media as a function of emotional expression and methods.Keywords: Emotional Expressions, Communication, Social Media, COVID-19, Photography Posts, Text, Instagram, Social Network, Attention Theory, Mental Health
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